Fault-Tolerance to Provide Robust Tracking for Autonomous and Non-Autonomous Positional Awareness

4. The system of claim 2, wherein a variance above a threshold indicates a moving platform; and a variance below a threshold indicates a static platform.

5. The system of claim 1, further configured for performing: detecting a number of updates from an inertial measurement unit (IMU) that measures and reports linear acceleration using one or more accelerometers and rotational rate using one or more gyroscopes, wherein the updating occurs after a successful image update; and switching to gyroscopic sensor propagation after N consecutive IMU updates are detected.

6. The system of claim 1, further configured for performing synchronizing time associated with at least one of the set of time dependent tracking states with a time maintained by a controller unit controlling the mobile platform, by updating the time associated with the time associated with at least one of the a set of time dependent tracking states by (i) a constant offset and (ii) a transfer delay.

8. The system of claim 7, wherein triangulating further includes selecting 3D points having a triangulation error less than a determined number of pixels.

9. The system of claim 7, further including adjusting a threshold for selecting 3d points to control propagation based upon a quantity of 3D points available to update poses in the set of time dependent tracking states.

10. The system of claim 7, further configured for performing dynamically determining a window size including a number of tracking states in the set of time dependent tracking states by maintaining a fixed manageable window size depending upon a parameter of at least one sensor.

11. The system of claim 7, further configured for performing dynamically determining a window size including a number of tracking states in the set of time dependent tracking states by maintaining a range of time spanning using the window size determined.

12. The system of claim 7, further configured for performing dynamically determining a window size including a number of tracking states in the set of time dependent tracking states by maintaining a manageable number of 3D points.

13. The system of claim 12, further configured for performing maintaining a number of 3D points in tracking states using a window size of less than 200.

14. The system of claim 7, further configured for performing refining 3D points using a least squares function.

15. The system of claim 7, further configured for performing: detecting a number of features in an image; and dynamically adjusting an exposure value of at least one visual sensor whenever a lack of features the image is detected.

16. The system of claim 7, further configured for performing: calculating a location of at least one 2D feature in an image using optical flow; reducing features to features existing along an epipolar line based upon a location calculated and a prediction of a camera pose; checking for similarity between descriptors of the feature and descriptors for a corresponding feature from a previous frame; determining whether number of features through optical flow is less than a number of features detected in a current frame, and whenever the number of features through optical flow is less than a number of features, detecting 2D corner features directly from an image at image regions without features; bin the image spatially, and adjust a number of features in each bin so that the number of features in the bins is balanced.

17. The system of claim 16, further configured for performing: linking features in different images captured at different times by a same camera.